• Guide and optimize spend so it scales efficiently under contribution margin guardrails • Define CAC ceilings tied to 12- and 24-month contribution margin • Model diminishing returns and marginal efficiency curves to inform budget allocation • Translate attribution constraints and measurement uncertainty into practical, decision-ready frameworks • Interpret insights from MMM, incrementality tests, lift studies, or MTA frameworks and translate them into practical budget and investment decisions • Identify which channels, audiences, creatives, and offers drive the highest-quality cohorts • Support structured validation of new channels before meaningful scale • Deliver clear monthly recommendations on where to scale, hold, or cut • Build and maintain 12- and 24-month contribution margin tracking by acquisition cohort • Develop survival curve diagnostics and retention performance visibility across key milestones • Operationalize retention-adjusted CAC and payback thinking into acquisition decisions • Identify acquisition sources that degrade churn, payback, LTV, or margin • Evaluate pricing, discounts, and offers against downstream margin impact • Create cohort-based forecasting views that improve decision quality without turning this role into FP&A • Own tracking health across ad platforms, GA4, server-side events, ecommerce, and subscription systems • Standardize UTMs, taxonomy, and core metric definitions so performance reporting is trusted • Partner with Finance to align revenue, refunds, COGS, and contribution margin inputs • Build automated dashboards and reduce manual reporting • Create a clear source of truth for acquisition efficiency and long-term cohort performance • Analyze tests and performance shifts across pricing, trial structure, billing cadence, onboarding, churn interventions, win-back, and upsell • Provide decision criteria rooted in long-term contribution margin, not isolated metric lifts • Deliver clear narratives on what changed, why it changed, and what to do next

• Develop and deploy scalable machine learning and AI solutions in production environments, ensuring performance and sustainability • Build and refine models for customer segmentation, risk prediction, clinical decision support, and other healthcare-specific use cases • Ensure rigorous use of statistical methods, reproducibility, and documentation across all projects • Design and implement statistical tests, A/B experiments, and performance monitoring strategies • Evaluate ML/AI models and products for fairness in output, targeting and actions • Partner with stakeholders to define problem statements, identify data sources, and design effective solutions • Build and maintain robust data pipelines, modeling workflows, and monitoring tools in collaboration with engineering and data platform teams • Partner with senior and executive leadership to define and advance the enterprise AI roadmap, identifying high-impact opportunities to embed ML and AI services into core business workflows • Lead multiple high-impact data science projects across areas including Clinical, STARs, Risk Adjustment, Claims, Pharmacy, Marketing and Member Experiences • Manage and mentor a team of data scientists; provide technical guidance via review of code, models, and analytical approaches; foster professional growth; and drive a culture of experimentation and continuous learning

Job Title: Language Data Scientist Location: Fully Remote within the U.S. (excluding California, Washington, Alaska, Colorado, Montana, New York, Puerto Rico, Nevada, Nebraska) Employment Type: Full-Time (40 hours per week) Fixed-Term Who we are: Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are an AI technology solutions provider-of-choice for 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine. By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of AI. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms. Our global workforce includes over 7,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re poised for a period of explosive growth over the next few years. About the Role: Innodata is building a team of Language Data Scientists and Gen AI experts to help our customers advance GenAI applications. You will work hands-on with multi-modal and multi-lingual datasets and collaborate with cross-functional partners. You will use your experience with human and synthetic data workflows to drive innovation and continuous improvement. The ideal candidate must have the right mix of skills in (computational) linguistics and human evaluation tasks, data science, and data engineering. Key Responsibilities: - Design/improve workflows to create data for AI/ML training and evaluation. Includes human annotation and data collection workflows, as well as synthetic ones. - Dive deep into existing workflows and processes to gather data and insights, make recommendations, and drive improvement through innovation and cross-functional collaboration with customers - Critically assess annotation tooling and workflows - Quantitatively analyze large datasets, perform statistical analysis, calculate metrics, and make recommendations to improve accuracy and performance - Work closely with client stakeholders on understanding goals, gathering requirements, proposing solutions and executing them. Qualifications: - Knowledge of how components of GenAI products or services combine to work - Collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals - MA in (computational) linguistics, data science, computer science (AI / ML / NLU), quantitative social sciences or a related scientific / quantitative field, PhD strongly preferred - Language and language data expertise: Extensive experience working with human language data and designing human evaluation tasks, including multi-phase and complex workflows. - Deep understanding of language and its relationship with culture - Ability to identify ambiguity and subjectivity in language - Ability to work with multi-lingual and multi-modal projects - Quantitative Analysis Skills: Advanced knowledge of statistics, metrics (e.g. f1 score, inter-rater reliability metrics), and data analysis methods such as sampling. - Technical skills: - Experience with Natural Language Processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face. - Proficiency in Python to - handle / transform large datasets (e.g. pre- and postprocessing data, pandas) - perform quantitative analyses - visualize data (for example matplotlib, seaborn) - Data processing: - Deep understanding of data pipelines to support ML and NLP workflows, - Knowledge of efficient data collection, transformation, and storage - Knowledge of data structures, algorithms, and data engineering principles - Excellent interpersonal skills for effective cross-functional stakeholder engagement - Excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions - Ability to work independently and collaborate as part of a team - Adaptable to changing technologies and methodologies - Ability to translate experience, research and development information to understand client products and services. Preferred Qualifications: - Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques - Knowledge of optimizing existing generative AI models for improved performance, scalability, and efficiency - Experience of developing and maintaining ML/AI pipelines, including data preprocessing, feature extraction, model training, and evaluation - Model Fine-Tuning: Knowledge of Fine-tuning pre-trained models to adapt them to specific tasks and datasets, improving their performance and relevance - Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and nontechnical stakeholders - Contributing to establishing best practices and standards for generative AI development with customers and within the organization - Providing technical mentorship and guidance to junior team members - Understanding of techniques such as GPT, VAE, and GANs Salary Range: Up to $95k USD Rates at Innodata vary depending on a wide array of factors, which may include but are not limited to the role, skill set, educational background and geographic location.

Attain Partners is an innovative consulting firm dedicated to disrupting the status quo to change the world and improve the lives of those we touch. From strategy to technology and everywhere in between, our experts use their unique skills to advance the important missions of education, nonprofit, healthcare, and state and local government clients. People are at the center of all we do, and that’s why we empower career growth, provide industry-leading benefits packages, encourage a flexible work environment, and foster a culture of inclusion to support the needs of our team. We share a collective passion for our mission and our people. Guided by our seven core values, The Attain Way, our vision is the foundation of our culture—to be and attain the best. Job Description Attain Partners is seeking an Integration & Data Leader responsible for designing, leading, and executing enterprise data integration and migration initiatives across client environments. This role focuses on SQL and SSIS based data movement, enterprise system integrations, and ensuring data accuracy, completeness, and alignment with business requirements during complex system transformations. The Integration & Data Leader partners closely with business stakeholders, architects, and technical teams to define integration requirements, map data across systems, and ensure high-quality data movement between platforms. This role also plays a critical part in helping organizations modernize their integration capabilities by evolving from traditional ETL-based architectures toward modern iPaaS platforms such as the Boomi Platform and other cloud integration tools. Job Responsibilities - Data Migration & Integration Leadership - Lead the migration and integration of enterprise data across systems using SQL, SSIS, and related data movement technologies. - Design and oversee data integration processes that support enterprise system interoperability. - Ensure data migrations are delivered with high levels of accuracy, completeness, and validation controls. - Coordinate the end-to-end lifecycle of data integrations including discovery, source-to-target mapping, build, testing, and deployment. - Requirements & Stakeholder Collaboration - Partner with business and technical stakeholders to gather integration requirements and understand system dependencies. - Define data attributes, transformation rules, and mapping logic necessary for successful integration. - Identify data quality risks and remediation strategies prior to integration or migration activities. - Facilitate integration discovery workshops and architecture discussions with client teams. - Integration Architecture & Delivery - Design scalable integration solutions leveraging SQL, SSIS, and enterprise integration patterns. - Oversee the development and execution of data pipelines, transformation logic, and integration workflows. - Ensure integrations align with enterprise architecture standards and system interoperability requirements. - Establish and maintain documentation including source-to-target mappings, integration specifications, and technical runbooks. - Data Quality & Governance Alignment - Identify and address data quality considerations during migration and integration processes. - Work with data governance teams to ensure integrations follow data standards and stewardship practices. - Implement validation and reconciliation processes to ensure data integrity across systems. - Modern Integration Enablement - Continuously expand technical capabilities by learning and adopting modern integration technologies and iPaaS platforms. - Support the organization’s transition from traditional ETL approaches toward cloud-based integration architectures. - Contribute to the development of modern integration frameworks and reusable patterns. Required Skills - 7+ years of experience in data integration, ETL development, or enterprise data migration. - Strong experience with SQL and SSIS for building and managing data pipelines. - Proven ability to lead complex data migration initiatives across enterprise systems. - Experience defining source-to-target mappings and data transformation rules. - Strong understanding of data quality practices, validation, and reconciliation techniques. - Ability to collaborate effectively with both business and technical stakeholders. - Strong documentation and communication skills for technical and functional audiences. Desired Skills - Experience with modern integration platforms (iPaaS) such as the Boomi Platform, MuleSoft, or similar tools. - Experience integrating with enterprise systems such as ERP, CRM, HRIS, and data warehouse platforms. - Consulting or professional services experience leading data integration workstreams. - Exposure to cloud data platforms, APIs, and modern integration architectures. - Experience in Higher Education Software Additional Information Attain Partners values your mental, emotional, and physical health and wellbeing. Our comprehensive benefits package starts on your first day of employment and includes benefits such as: - Competitive health, dental, and vision coverage, HSA and FSA accounts, life and disability insurance, fertility and family planning benefits, and employee assistance and discount programs - 11 paid federal holidays and flexible unlimited time off (UTO) - Generous 401(k) matching with immediate vesting - Flexible career paths – our career tracks provide advancement, mobility, and flexibility as you continue to grow with us - A healthy environment where we value unique experiences, and care about everything that makes you, you. Attain Partners is committed to fair and equitable compensation practices. The individual base salary for this position is unique to each candidate and will be commensurate with experience, education, and skills. In addition to base salary, this role is eligible for an annual discretionary bonus. Interested in this position but the compensation isn’t quite right? Let us know your expectations, and we’ll see if we can make it happen based on your qualifications. Salary Range $160,000—$170,000 USD Attain Partners is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. Applicants have rights under Federal Employment Laws. For more Information visit EEO, EEO Poster Supplement, Family and Medical Leave Act (FMLA), and Employee Polygraph Protection Act (EPPA). If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.